In a wireless communication system, a receiver receives signals which include both signals intended for the specific receiver and signals intended for other receivers operating within the same frequency band. The signals intended for other receivers are referred to as interference. There are also sources of noise which produce signals that are not used for communication, but are received by the specific receiver as well. The general formula for a received signal incident to an antenna element is expressed as follows:x=s+ΣIi+Σnk;   Equation (1)where x is sum of signals of all types, s is signal of interest, ΣIi is interference due to other communication signals of known characteristics and Σnk is noise due to sources of unknown characteristics.
The capacity of a communication channel is limited by the Shannon's formula:C=W log2(1+S/N);   Equation (2)where C is capacity in bits per second, W is channel bandwidth in Hertz, S is the desired signal power and N is the power of all components not of interest which includes interference and noise.
The signal-to-noise ratio, S/N, in Equation (2) can be replaced by a signal-to-interference plus noise ratio (SINR) which is defined as follows:
                                                        SINR              =                            ⁢                                                Communication_Signal                  ⁢                  _Of                  ⁢                                      _Interest                    2                                                                                                                                                                ∑                                                      All_Other                            ⁢                            _Communication                            ⁢                                                          _Signals                              2                                                                                                      +                                                                                                                                                ∑                                                  All_Noise                          ⁢                                                      _Signals                            2                                                                                                                                                                                                                                      =                                ⁢                                                      s                    2                                                                              ∑                                              I                        i                        2                                                              +                                          ∑                                              n                        k                        2                                                                                                        ;                                                          Equation        ⁢                                  ⁢                  (          3          )                    The channel capacity is therefore C=W log2(1+SINR). Assuming a fixed allocation of bandwidth, W, it would be desirable to increase the value of SINR in order to maximize the capacity of the communication channels.
A conventional approach to increase the value of SINR is to exploit known characteristics of the signals by extracting them from the received signals, (i.e., non-blind technique). Training sequences are often used to allow the receiver to determine how to differentiate the signal of interest from all other signals. While the signal of interest may be the desired signal for further processing, (e.g., data extraction or location determination), the signal of interest may be one of the other signals in the received signal sum. In the latter case, determining such a signal may facilitate its subtraction from the received signals, leading to a more robust extraction of the desired signal for utilization. When available, this type of processing is often the preferred approach to extract the desired signal, subject to other system level considerations such as computational complexity, channel variation, or the like.
Successive interference cancellation (SIC) is an example of a non-blind interference cancellation technique. The SIC is based on knowledge of the signals that is either known or determined. FIG. 1 shows an exemplary conventional receiver 100 implementing SIC. In the receiver 100, received baseband data 101 is stored in a buffer 102. Interference is subtracted from the stored received baseband data, or the baseband data is ‘orthogonally-projected’ to the interference signals. The processed data output of the buffer 102 is multiplied with a scrambling code conjugate by a plurality of multipliers 104A-104L and correlated with L codes by a plurality of fast Walsh transformers (FWTs) 106A-106L. The outputs from the FWTs 106A-106L are combined by a maximal ratio combiner (MRC) 108. One of N outputs is selected by a decision unit 110 as an output and maximum M values selected by a selection unit 112 from N-1 outputs are fed back to the buffer 102 via a signal regeneration unit 114 which cancels the M signals as interference. The M signals are spread again by spreaders 116a-116M and summed by a summer 118. The summed signal is multiplied with a scrambling code by a multiplier 120 and the multipath channel signal is regenerated by the signal regenerator 122. The regenerated signal is subtracted from the received data 101 stored in the buffer 102 as the interference.
Another conventional approach to signal extraction is a class of signal processing referred to as blind signal processing. The term “blind” refers to the fact that the signals are separated without some information required by the conventional techniques exploiting known characteristics of the signals. For example, a lack of a training sequence or inability to decode it due to excessive signal distortion does not allow comparison of a known signal to a received signal. Therefore, the channel effects on the transmitted signal can not be directly determined.
Blind signal separation techniques get around this lack of information by exploiting information that still exists in the various signal types. One such type of information is the moment of a signal. Different communications stream sources impart different values to these moments. By maximizing a cost function based on the unique values of these parameters due to each signal, a separation matrix may be determined which will extract each signal from the mixture. Independent component analysis (ICA) and principle component analysis (PCA) are examples of blind signal separation methods.
Both the non-blind and blind techniques have their appropriate applications. When there is knowledge concerning the signal components, a non-blind technique is usually the more robust one to utilize, although the blind technique may also work. When the knowledge is not available, the blind technique should be used.
The non-blind and blind techniques have been jointly employed in receive processing only to a limited degree. One example is outlined in a paper entitled “Inter-Cell Interference Cancellation in CDMA Array Systems by Independent Component Analysis”, (available from web site http://www.kecl.ntt.co.jp/icl/signal/ica2003/). FIG. 2 is a block diagram of a receiver 200 in accordance with this approach. In FIG. 2, signal aggregates from different cells are separated by an ICA unit 202. A separated aggregate containing the data for the receiver 200 is then selected by a selection unit 204 and the selected data alone is fed to a first Rake processing block 206 which is a non-blind approach as it exploits the spreading codes. The selection unit 204 is necessary since the ICA processing can output the separated signals in an initially unknown order. The selection unit 204 performs a minimal amount of processing to identify the target stream. For example, this may be performed by decoding a portion of the stream which should produce a known sequence of data, or have a specific set of signal characteristics. The stream which best satisfies the criteria is selected by the selection unit 204. The received signal may be processed only by a second Rake processing block 208 via a pre-switch 210 and a post switch 212. The two Rake processing blocks 206, 208 may be the same processing block.
While this approach is beneficial, it does not always work as exemplified by the figure illustrating the selection of its use or the avoidance of the ICA portion of the processing. This is because under certain circumstances the ICA processing actually has a detrimental overall effect on the extracted signal quality. An example of this problem is when the product of the separation matrix and the noise exceeds the gains from the separation of the signals. Therefore, a means to obtain consistent and robust SINR improvements is desirable.